An output feedback tracking control based on neural sliding mode and high order sliding mode observer

Vo, Anh Tuan; Nguyen, Van-Cuong

doi:10.1109/hsi.2017.8005020

Cited by 22 publications

(6 citation statements)

References 13 publications

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“…To overcome these challenges, many types of SMC and TSMC have been suggested based on ACs because they can automatically adapt the control parameters to reject the influences of environmental disturbances, uncertainties, or faults [42], [58]- [61]. And, to approximate unknown nonlinear functions, several computing attempts have been suggested, such as Neural Networks (NNs) [23], [39], [62], [63] and Fuzzy Logic Systems (FLSs) [22], [64], due to their approximation capabilities. However, using NNs or FLSs to approximate unknown nonlinear functions lead to increases the complex calculations for the control system.…”

Section: Introductionmentioning

confidence: 99%

A Novel Fault-Tolerant Control Method for Robot Manipulators Based on Non-Singular Fast Terminal Sliding Mode Control and Disturbance Observer

2020

IEEE Access

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In this study, a novel Fault-Tolerant Control Methodology (FTCM) is developed for robot manipulators. First, to overcome singularity glitch and to enhance convergence time of conventional Terminal Sliding Mode Control (TSMC), a new Fast Terminal Sliding Mode Surface (FTSMS) is constructed. Next, to reduce the computation complexity and to provide requirements about undefined nonlinear functions for the control system, a Disturbance Observer (DO) to estimate uncertain dynamics, external disturbances, or faults. Besides, a Super-Twisting Reaching Control Law (STRCL) is designed to compensate for the estimated error of disturbance observer with chattering rejection. Final, a novel, robust, FTCM was developed for robot manipulators to obtain the stability goal of the system, to reach the prescribed performance, and to overcome the effects of disturbances, nonlinearities, or faults. Accordingly, the proposed FTCM has remarkable features, such as fast convergence speeds, robust precision, high tracking performance, significant alleviation of chattering behavior, and finite-time convergence. The position tracking computer simulations were implemented to exhibit the effectiveness and feasibility of the suggested FTCM compared with other control algorithms.

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Section: Introductionmentioning

confidence: 99%

A Novel Fault-Tolerant Control Method for Robot Manipulators Based on Non-Singular Fast Terminal Sliding Mode Control and Disturbance Observer

2020

IEEE Access

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“…Schenk et al 21 extended the sliding mode controller through feedforward dynamic inverse control for the redundant cable-driven parallel manipulator, which reduced the workload of the sliding mode controller and weakened the chattering phenomenon. Vo et al 22 designed a disturbance observer based on sliding mode control to identify and compensate for the disturbance, which greatly reduced the gain of the required switching function, weakened the chattering phenomenon and improved the tracking performance. Wang et al 23 proposed a controller composed of sliding mode control, fuzzy control, and low-pass filter to reduce the high-frequency chattering control signal in the sliding mode control.…”

Section: Introductionmentioning

confidence: 99%

The adaptive neural network fuzzy sliding mode control for the 3-RRS parallel manipulator

Li¹,

Gao²,

Sun³

et al. 2022

Advances in Mechanical Engineering

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In order to improve the high-precision tracking control of angle variables and the sliding mode equivalent control part for the 3-RRS parallel manipulator, an adaptive neural network fuzzy sliding mode control algorithm with self-adjusting switching gain is proposed. Firstly, considering the uncertainty of the constrained force between derived links and the moving platform, the complete dynamic model including ideal and non-ideal constrained force is established by combining with the Udwadia-Kalaba(U-K) equation and Lagrange method. Secondly, the neural network sliding mode controller is designed to realize the approximate solution of the sliding mode equivalent control part. At the same time, in order to reduce the chattering phenomenon of the neural network sliding mode controller, a fuzzy adjustment rule of switching gain is designed to better compensate for the uncertain terms. And then the stability of the control system is proved by the Lyapunov method. Finally, the proposed control algorithm is simulated on the 3-RRS parallel manipulator. The simulation results show that the chattering phenomenon is overcome. The high-precision control of angle variables and the sliding mode equivalent control part is realized.

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“…Unfortunately, those controllers do not exhibit good control performance of highly nonlinear and uncertain control systems. Accordingly, to handle the uncertainty of robotic systems and to improve the control performance, recently, many nonlinear methods have been suggested for robot manipulators such as adaptive control [3], [4], fuzzy control [5], [6], optimal control [7], neural network control [8], [6], and sliding mode control [9]- [12].…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Terminal Sliding Mode Control for Robot Manipulators With Non-Singular Terminal Sliding Surface Variables

Kang

2019

IEEE Access

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This paper presents an adaptive terminal sliding mode control (TSMC) algorithm for robot manipulators. The contribution of our control method is that the suggested controller can enable the advantages of non-singular TSMC such as non-singularity, high robustness, small transient error, and finite time convergence. To develop the suggested system, a non-singular terminal sliding variable is selected and does not have any complex-value or constraints of the exponent in conventional TSMC. Therefore, it prevents the singularity that occurs in the conventional TSMC and eliminates the reaching phase glitch. Accordingly, the suggested system can ensure that the controlled variables reach the desired values within a randomly known finite time using an efficiently smooth and chattering-free definite control input. In addition, sliding motion in finite time can be achieved by employing the adaptive self-tuning rules with no prior information regarding the upper bounds of undefined parameters (e.g., friction, disturbances, and uncertainties). Furthermore, the finite-time convergence and global stability of the proposed algorithm are proved by the Lyapunov stability theory. Finally, the proposed control algorithm is applied to the joint position tracking control simulation for a 3-DOF PUMA560 robot. The trajectory tracking performance of the proposed method is compared with those of the conventional terminal sliding mode control and the conventional continuous sliding mode control. This comparison shows the efficiency and superiority of the proposed algorithm. INDEX TERMS Non-singular terminal sliding mode control, robotic manipulator, adaptive self-tuning rules, uncertainty, disturbance, chattering behavior.

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An output feedback tracking control based on neural sliding mode and high order sliding mode observer

Cited by 22 publications

References 13 publications

A Novel Fault-Tolerant Control Method for Robot Manipulators Based on Non-Singular Fast Terminal Sliding Mode Control and Disturbance Observer

A Novel Fault-Tolerant Control Method for Robot Manipulators Based on Non-Singular Fast Terminal Sliding Mode Control and Disturbance Observer

The adaptive neural network fuzzy sliding mode control for the 3-RRS parallel manipulator

An Adaptive Terminal Sliding Mode Control for Robot Manipulators With Non-Singular Terminal Sliding Surface Variables

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